System Identification

System Identification

Deep networks have set new standards for accurately predicting responses of neurons in visual cortex to arbitrary images. However, these models still do not account for all the explainable variability of the neuronal responses in primary visual cortex. We are building better models for the visual system of mice and monkeys that can accurately predict responses and their per trial variability as well as estimate the general state that the brain was in during presentation of arbitrary visual inputs.


Publications

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2023

Konstantin-Klemens Lurz1, Mohammad Bashiri1, Edgar Y. Walker, Fabian H. Sinz Bayesian Oracle for bounding information gain in neural encoding models ICLR 2023 (accepted) , equal contribution: 1

2022

Erick Cobos, Taliah Muhammad, Paul G Fahey, Zhiwei Ding, Zhuokun Ding, Jacob Reimer, Fabian H. Sinz, Andreas Tolias It takes neurons to understand neurons: Digital twins of visual cortex synthesize neural metamers biorXiv
Konstantin Lurz, Mohammad Bashiri, Fabian Sinz Bayesian Oracle for bounding information gain in neural encoding models Neurips 2022 Workshop InfoCog
workshop paper · system identification ·
Luca Baroni1, Mohammad Bashiri1, Konstantin Friedrich Willeke, Ján Antolík, Fabian Sinz Learning Invariance Manifolds of Visual Sensory Neurons Neurips 2022 Workshop NeurReps , equal contribution: 1
Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri, Laura Pede, Max F. Burg, Christoph Blessing, Santiago A. Cadena, Zhiwei Ding, Konstantin-Klemens Lurz, Kayla Ponder, Taliah Muhammad, Saumil S. Patel, Alexander S. Ecker, Andreas S. Tolias, Fabian H. Sinz The Sensorium competition on predicting large-scale mouse primary visual cortex activity arXiv

2021

Mohammad Bashiri, Edgar Y. Walker, Konstantin-Klemens Lurz, Akshay Kumar Jagadish, Taliah Muhammad, Zhiwei Ding, Zhuokun Ding, Andreas S. Tolias, Fabian H. Sinz A flow-based latent state generative model of neural population responses to natural images NeurIPS (spotlight)
Max F. Burg, Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker Learning Divisive Normalization in Primary Visual Cortex PLoS Computational Biology
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Friedrich Willeke, Akshay Kumar Jagadish, Eric Wang, Edgar Y Walker, Santiago Cadena, Taliah Muhammad, Eric Cobos, Andreas Tolias, Alexander Ecker, Fabian Sinz Generalization in data-driven models of primary visual cortex ICLR (spotlight)

2020

James R. Cotton, Fabian H. Sinz, Andreas S. Tolias Factorized Neural Processes for Neural Processes: K-Shot Prediction of Neural Responses NeurIPS
Ivan Ustyuzhaninov, Santiago A. Cadena, Emmanouil Froudarakis, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Fabian H. Sinz, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker Rotation-invariant clustering of functional cell types in primary visual cortex ICLR (accepted for talk)
conference paper · system identification · openreview

2019

Santiago A. Cadena, Fabian H. Sinz, Taliah Muhammad, Emmanouil Froudarakis, Erick Cobos, Edgar Y. Walker, Jake Reimer, Matthias Bethge, Andreas Tolias, Alexander S. Ecker How well do deep neural networks trained on object recognition characterize the mouse visual system? NeurIPS workshop on Real Neurons & Hidden Units (accepted for talk)
Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis, Paul G. Fahey, Santiago A. Cadena, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Andreas S. Tolias, Matthias Bethge A rotation-equivariant convolutional neural network model of primary visual cortex ICLR 2019
S. A. Cadena, G. H. Denfield, E. Y. Walker, L. A. Gatys, A. S. Tolias, M. Bethge, and A. S. Ecker Deep convolutional models improve predictions of macaque V1 responses to natural images PLoS Computational Biology
journal paper · system identification · PLoS

2018

Fabian H. Sinz, Alexander S. Ecker, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Emmanouil Froudarakis, Dimitri Yatsenko, Xaq Pitkow, Jacob Reimer, Andreas S. Tolias Stimulus domain transfer in recurrent models for large scale cortical population prediction on video NeurIPS